Normalisation of measured energy consumption to inform both design and operational decisions

Massimiliano Manfren1, Giorgia Marenzi2, Lavinia Chiara Tagliabue3, Giuseppe Martino Di Giuda3, Marta Boscariol3
1 University of Southampton
2 Politecnico di Milano, Italy
3 University of Turin
DOI: 10.35490/EC3.2023.252
Abstract: The building sector is one of the most resource-intensive sectors and a significant contributor to carbon emissions in the European Union and on a global scale. In this study, 10 public buildings in the northern Italian city of Melzo were analysed and modelled in order to determine which tools can be used to address the above-mentioned challenges while streamlining and partially automating the process of building stock digitalisation, even in the presence of limited information.
Keywords: building energy modelling, Data-driven methods, energy efficiency, interpretable machine learning, measurement and verification

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